Understanding E-Scooter Incidents Patterns in Street Network Perspective: A Case Study of Travis County, Texas

Junfeng Jiao, Shunhua Bai and Seung Jun Choi
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Junfeng Jiao: Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA
Shunhua Bai: Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA
Seung Jun Choi: Urban Information Lab., The School of Architecture, The University of Texas at Austin, Austin, TX 78705, USA

Sustainability, 2021, vol. 13, issue 19, 1-13

Abstract: Dockless electric scooter (E-scooters) services have emerged in the United States as an alternative form of micro transit in the past few years. With the increasing popularity of E-scooters, it is important for cities to manage their usage to create and maintain safe urban environments. However, E-scooter safety in U.S. urban environments remains unexplored due to the lack of traffic and crash data related to E-scooters. Our study objective is to better understand E-scooter crashes from a street network perspective. New parcel level street network data are obtained from Zillow and curated in Geographic Information System (GIS). We conducted local Moran’s I and independent Z-test to compare where and how the street network that involves E-scooter crash differs spatially with traffic incidents. The analysis results show that there is a spatial correlation between E-scooter crashes and traffic incidents. Nevertheless, E-scooter crashes do not fully replicate characteristics of traffic incidents. Compared to traffic incidents, E-scooter incidents tend to occur adjacent to traffic signals and on primary roads.

Keywords: e-scooter safety; micro-mobility; street network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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